Brain-computer interface(BCI) was a communication system that did not depend on the brain's normal output pathways of the peripheral nerves and muscles.BCI provided a new communication channel for the patients with severe neuromuscular disorders,and also had potential values in virtual reality,entertainment and aviation.Recently,BCI developed rapidly,and its researches mostly concentrated on feature extraction and translation algorithm.Cortical evoked potentials such as steady-state visual evoked potential(SSVEP) and P300 were widely applied in BCI because of simple feature extraction and requiring little training.The progress in SSVEP-based and P300-based BCI was reviewed,and its experimental paradigms and limitations were analyzed in this paper.

This project studied the historical and the present situation about the personnel training model in medical education and its structure. It reestablished the objectives of the medical education and the standards of the training, modified the training program, and the curriculum system, and set up the new teaching plan and syllabus. Through three years of research and implementation, the training model of widening the basic science, breaking into three stages, integrating the courses, optimizing three phases, activating teaching methods and total adaptability had been constructed.And the project had been studied, applied and spread cooperatively with 16 Chinese medical schools.

Objective: To improve the N biomarker in the amyloid/taueurodegeneration system by radiomics and study its value for predicting cognitive progression in individuals with mild cognitive impairment (MCI). Materials and Methods: A group of 147 healthy controls (HCs) (72 male; mean age ± standard deviation, 73.7 ± 6.3 years), 197 patients with MCI (114 male; 72.2 ± 7.1 years), and 128 patients with Alzheimer’s disease (AD) (74 male; 73.7 ± 8.4 years) were included. Optimal A, T, and N biomarkers for discriminating HC and AD were selected using receiver operating characteristic (ROC) curve analysis. A radiomics model containing comprehensive information of the whole cerebral cortex and deep nuclei was established to create a new N biomarker. Cerebrospinal fluid (CSF) biomarkers were evaluated to determine the optimal A or T biomarkers. All MCI patients were followed up until AD conversion or for at least 60 months. The predictive value of A, T, and the radiomics-based N biomarker for cognitive progression of MCI to AD were analyzed using Kaplan-Meier estimates and the log-rank test. Results: The radiomics-based N biomarker showed an ROC curve area of 0.998 for discriminating between AD and HC. CSF Aβ42 and p-tau proteins were identified as the optimal A and T biomarkers, respectively. For MCI patients on the Alzheimer’s continuum, isolated A+ was an indicator of cognitive stability, while abnormalities of T and N, separately or simultaneously, indicated a high risk of progression. For MCI patients with suspected non-Alzheimer’s disease pathophysiology, isolated T+ indicated cognitive stability, while the appearance of the radiomics-based N+ indicated a high risk of progression to AD. Conclusion We proposed a new radiomics-based improved N biomarker that could help identify patients with MCI who are at a higher risk for cognitive progression. In addition, we clarified the value of a single A/T/N biomarker for predicting the cognitive progression of MCI.

Mantle cell lymphoma (MCL) is a distinct histological type of B-cell lymphoma with a poor prognosis. Several agents, such as proteasome inhibitors, immunomodulatory drugs, and inhibitors of B cell lymphoma-2 and Bruton's tyrosine kinase have shown efficacy for relapsed or refractory (r/r) MCL but often have short-term responses. Chimeric antigen receptor (CAR) T-cell therapy has emerged as a novel treatment modality for r/r non-Hodgkin's lymphoma. However, long-term safety and tolerability associated with CAR T-cell therapy are not defined well, especially in MCL. In this report, we described a 70-year-old patient with r/r MCL with 48-month duration of follow-up who achieved long-term remission after CAR T-cell therapy. CAR T-cell-related toxicities were also mild and tolerated well even in this elderly patient. This report suggested that CAR T-cell therapy is a promising treatment modality for patients with MCL, who are generally elderly and have comorbid conditions.
Adult ; Aged ; Cell- and Tissue-Based Therapy ; Humans ; Immunotherapy, Adoptive ; Lymphoma, Mantle-Cell/therapy* ; Neoplasm Recurrence, Local ; Receptors, Chimeric Antigen

The mammalian brain is heterogeneous, containing billions of neurons and trillions of synapses forming various neural circuitries, through which sense, movement, thought, and emotion arise. The cellular heterogeneity of the brain has made it difficult to study the molecular logic of neural circuitry wiring, pruning, activation, and plasticity, until recently, transcriptome analyses with single cell resolution makes decoding of gene regulatory networks underlying aforementioned circuitry properties possible. Here we report success in performing both electrophysiological and whole-genome transcriptome analyses on single human neurons in culture. Using Weighted Gene Coexpression Network Analyses (WGCNA), we identified gene clusters highly correlated with neuronal maturation judged by electrophysiological characteristics. A tight link between neuronal maturation and genes involved in ubiquitination and mitochondrial function was revealed. Moreover, we identified a list of candidate genes, which could potentially serve as biomarkers for neuronal maturation. Coupled electrophysiological recording and single cell transcriptome analysis will serve as powerful tools in the future to unveil molecular logics for neural circuitry functions.
Antigens, Differentiation ; biosynthesis ; Electrophysiological Phenomena ; physiology ; Gene Expression Regulation ; physiology ; Genome-Wide Association Study ; Human Embryonic Stem Cells ; cytology ; metabolism ; Humans ; Induced Pluripotent Stem Cells ; cytology ; metabolism ; Multigene Family ; physiology ; Neurons ; cytology ; metabolism ; Transcriptome ; physiology